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All Journal TEKNIK INFORMATIKA Sainteks Jurnal Pseudocode SMATIKA Jurnal Ilmiah KOMPUTASI Jurnal Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA InComTech: Jurnal Telekomunikasi dan Komputer Jurnal SOLMA Prosiding Seminar Nasional Teknoka Dinamisia: Jurnal Pengabdian Kepada Masyarakat SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal Sisfokom (Sistem Informasi dan Komputer) IJID (International Journal on Informatics for Development) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Linguistik Komputasional Jurnal ICT : Information Communication & Technology Building of Informatics, Technology and Science FIKROH: JURNAL PEMIKIRAN DAN PENDIDIKAN ISLAM Jurnal Teknologi Dan Sistem Informasi Bisnis Zonasi: Jurnal Sistem Informasi Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Asiimetrik: Jurnal Ilmiah Rekayasa Dan Inovasi JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Sistem Komputer dan Informatika (JSON) Infotech: Journal of Technology Information Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Teknik Informatika (JUTIF) KLIK: Kajian Ilmiah Informatika dan Komputer Sibatik Journal : Jurnal Ilmiah Bidang Sosial, Ekonomi, Budaya, Teknologi, Dan Pendidikan Jurnal Penyuuhan dan Pemberdayaan Masyarakat (JPPM) STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer SmartComp Fikroh: Jurnal Pemikiran dan Pendidikan Islam JURNAL TEKNIK INFORMATIKA DAN KOMPUTER Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) SAMBARA: Jurnal Pengabdian Kepada Masyarakat Cosmic Jurnal Teknik BHAKTI JIVANA Smatika Jurnal : STIKI Informatika Jurnal
Firman Noor Hasan
Universitas Muhammadiyah Prof. Dr. Hamka
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Analisis Sentimen Tanggapan Pengguna Aplikasi Bale by BTN Menggunakan Metode Support Vector Machine (SVM) Setiawan, Ahmat; Hasan, Firman Noor
STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Vol. 4 No. 4 (2025): November
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/storage.v4i4.6469

Abstract

Dalam era digital yang kian berkembang, analisis sentimen pada komentar pengguna dijadikan alat penting untuk mengevaluasi kualitas aplikasi mobile banking. Penelitian ini bertujuan untuk mengidentifikasi sentimen pengguna pada aplikasi bale by BTN yang diluncurkan pada Februari 2025 sebagai penyempurna dari aplikasi BTN Mobile. Metode yang digunakan meliputi scraping data ulasan dari Google Play Store, preprocessing teks (case folding, normalisasi, tokenisasi, stopword removal, dan stemming), pelabelan berdasarkan kamus lexicon-based approach, serta pembangunan klasifikasi model dengan algoritma Support Vector Machine dengan TF-IDF vectorization. Dari 2.000 data awal, diperoleh 1.767 data valid yang dianalisis. Hasil menunjukkan bahwa model SVM mencapai akurasi sebesar 73,16%, dari 354 data testing dengan distribusi sentimen: positif (52,57%), dan negatif (47,43%). Model menunjukkan performa terbaik dalam mengklasifikasi sentimen Positif dengan precision 0.73, recall 0.80, dan F1-score 0,77 pada 194 data sedangkan pada sentimen negatif, model menunjukan hasil cukup baik dengan precision 0.73, recall 0.65, dan F1-score 0.69 pada 160 data.
Analisis Sentimen Terhadap Kandidat Calon Presiden Berdasarkan Tweets Di Sosial Media Menggunakan Naive Bayes Classifier Allif Rizki Abdillah; Firman Noor Hasan
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 13 No 01 (2023): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v13i01.750

Abstract

This research is to analyze the sentiments of the Indonesian people about the presidential candidates who are likely to advance in the 2024 presidential election from tweets on the Twitter application. Tweets on Twitter are written, typed and published by Indonesian netizens about the candidates who are likely to advance in the 2024 presidential election. In this study, researchers used tools, namely RapidMiner Studio to collect tweet data from Indonesian netizens about the candidates. Furthermore, the researcher uses the Naïve Bayes Classifier algorithm to determine whether a statement or sentiment has a positive or negative value which is carried out using Rapid Miner tools as well. Of the four candidates that the researchers examined, Anies got 74% positive sentiment 26% negative sentiment, then followed by Sandi, namely 57% positive sentiment 43% negative sentiment, Ganjar received 53% positive sentiment 47% negative sentiment and Prabowo received 32% positive sentiment. 68% negative sentiment. The conclusion of this research is to find out which candidates are liked or favored by the Indonesian people from the results of sentiment analysis using the Naïve Bayes algorithm and the tools used, namely Rapid Miner.
Analisis Sentimen Masyarakat Mengenai RUU Perampasan Aset Di Twitter Menggunakan Metode Naïve Bayes kivandi Nugroho; Firman Noor Hasan
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 13 No 02 (2023): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v13i02.899

Abstract

The development of the world is growing especially in social media, one of which is Twitter. Twitter itself is a social media that can be accessed by various groups to communicate, besides that there are various kinds of public opinions that are quite varied. Data collection from Twitter can be used to conduct sentiment analysis in order to find out public opinion. The research conducted by researchers is an analysis of public sentiment regarding RUU Perampasan Aset that has never been passed. This research starts from data collection, processing, data implementation and evaluation using rapidminer tools. In the data retrieval process, researchers used the keyword "RUU Perampasan Aset", the data that was successfully obtained was 413, which was then processed at the Preprocessing stage so that later it could be analyzed using the naïve bayes method in this process 179 data were obtained. The results obtained in the form of positive and negative analysis of RUU Perampasan Asetl, obtained as many as 131 or 73% positive comments and only 48 or 27% negative comments. For positive class precision 90%, and class recall of 55%, while for negative class precision 42%, and class recall of 85%, with accuracy obtained at 63%.
Sentiment Analysis on Shopee Xpress Delivery Time Reviews Using Support Vector Machine and Logistic Regression Sewin Fathurrohman; Irfan Ricky Afandi; Irma Wahyuningtyas; Azis Styo Nugroho; Firman Noor Hasan
IJID (International Journal on Informatics for Development) Vol. 14 No. 2 (2025): IJID December
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2025.5073

Abstract

This study examines user sentiment towards Shopee Xpress delivery times using machine learning techniques. We collected 497 reviews from platforms like X and the Google Play Store, leveraging the valuable feedback despite its unstructured and informal nature. After labelling 398 reviews for model training and reserving 99 for sentiment prediction, we implemented two classification algorithms: Support Vector Machine (SVM) and Logistic Regression. These models categorised sentiments into negative, neutral, and positive classes. Despite class imbalance in the training data, SVM outperformed Logistic Regression with an accuracy of 93%, demonstrating a more balanced performance across sentiment categories compared to Logistic Regression's 90% accuracy. Both models showed consistent sentiment prediction on new data. Our findings highlight the potential of sentiment analysis as a valuable tool for Shopee Xpress to understand customer perceptions and improve delivery experiences. By providing actionable insights, this study can inform logistics improvements and enhance customer satisfaction. Future research could benefit from collaborating with Shopee to access internal data and integrating additional data sources for more comprehensive insights, ultimately driving business growth and customer loyalty. This study contributes to the growing body of research on sentiment analysis in logistics and e-commerce.
Rancang Bangun Sistem Penebar Pakan Ikan berbasis Internet of Things (IoT) Ridwan Bagus Andreyanto; Gusnul Mahesa; Muhammad Rizal; Lutfi Triyuli Evana Rizki; Firman Noor Hasan
Prosiding Seminar Nasional Teknoka Vol 10 (2025): Proceeding of TEKNOKA National Seminar - 10
Publisher : Fakultas Teknik, Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In everyday life, both in urban and rural areas, many people enjoy keeping fish as pets because they are easy to care for and maintain. This has led to a growing interest in fishkeeping among the general public. Fish kept in aquariums require regular feeding schedules to maintain their health, making an organized and consistent feeding system essential. The ESP32 is an integrated chip developed for modern networking applications. It provides a complete and integrated Wi-Fi networking solution that can function as an application processor or serve as a Wi-Fi network controller for other processors. One of its practical applications is in the development of an automatic fish feeder based on the Internet of Things (IoT). By utilizing the ESP32 along with supporting software such as Arduino IDE, Google Firebase, and MIT App Inventor, the automatic fish feeder can operate automatically according to predefined feeding schedules. Furthermore, the system can send notifications through a website when the fish have been fed or when the feed container is empty.
Implementasi Teknik Clustering untuk Meningkatkan Performa Aplikasi Node JS Rozak, Bahrul; Erizal, Erizal; Hasan, Firman Noor
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 12, No 4 (2023): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v12i4.4532

Abstract

Permasalahan yang sering kali muncul pada aplikasi berbasis server side, adalah request request dan response dalam jumlah yang besar. Proses request serta response akan terus berlanjut selama pengguna berinteraksi dengan aplikasi, Jika hal ini terus berlanjut maka penggunaan sumber daya (resource) yang berlebih pada CPU dapat menjadikan perfoma aplikasi tidak optimal bahkan dapat menimbulkan crash, yang berdampak pada layanan dan kualitas aplikasi. Oleh karena itu, diperlukan teknik untuk menangani permasalahan tersebut. Metode yang diimplementasikan pada penelitian ini ialah membuat aplikasi berbasis server side dengan dua spesifikasi yaitu dengan module cluster dan tanpa module cluster, selanjutnya kedua aplikasi dengan spesifikasi yang berbeda, masing-masing akan dilakukan tahap pengujian performa serta monitoring, kemudian dilakukan proses analisa hasil perbandingan untuk mendapatkan kesimpulan. Module cluster akan membantu untuk melakukan teknik clustering, teknik clustering ialah mengelompokkan proses yang sama serta sering dieksekusi. Dengan teknik ini beban kerja pada CPU akan terdistribusi, sehingga memberikan peningkatan performa aplikasi.
Analisis Sentimen Opini Masyarakat Terhadap Keefektifan Pembelajaran Daring Selama Pandemi COVID-19 Menggunakan Naïve Bayes Classifier Ari Wibowo; Firman Noor Hasan; Luthfi Akbar Ramadhan; Rika Nurhayati; Arief Wibowo
Jurnal Asiimetrik: Jurnal Ilmiah Rekayasa Dan Inovasi Volume 4 Nomor 2 Tahun 2022
Publisher : Fakultas Teknik Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/asiimetrik.v4i1.3577

Abstract

Since Indonesia was affected by the Covid-19 pandemic, one of the sectors affected was Education. The government makes an online learning system policy where the system is run with an online process. Not a few of them complained about the limitations of activities issued by the government. Twitter social media is often used to express opinions about concerns about programs issued by the government. The Twitter data crawling process was carried out using the hashtag "learning from home" to get as many as 1,000 datasets, followed by the process of removing duplicates which left 524 datasets and then carrying out the implementation stage of the Naïve Bayes Classifier Algorithm. The purpose of this study was to determine the number of positive and negative sentiments from the dataset labeling classification and to determine the accuracy results of using the Naïve Bayes Classifier method as well as the results of evaluation tests on positive and negative sentiment datasets. Based on the experiment, positive sentiment was obtained as many as 480 and negative sentiment as many as 44 out of 524 datasets. The accuracy results in the evaluation test process get results of 88.5% where negative sentiments get a precision value of 12%, recall 17%, and f1-score 14%, while positive sentiments get a precesion value of 95%, recall 93%, and f1 -score 94%.
The Influence of Simping Clamshell Addition on Disc Brake Pad Mechanical Properties: Pengaruh Penambahan Kulit Kerang Simping terhadap Sifat Mekanik pada Kampas Rem Cakram Agus Fikri; Firman Noor Hasan; Riyan Ariyansah
Jurnal Asiimetrik: Jurnal Ilmiah Rekayasa Dan Inovasi Volume 5 Nomor 2 Tahun 2023
Publisher : Fakultas Teknik Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/asiimetrik.v5i2.4984

Abstract

The brake pads made from asbestos are environmentally hazardous due to the friction and abrasion occurring during braking, resulting in the release of airborne asbestos fibers. These fibers pose various health risks to humans and contribute to environmental pollution. This study aims to analyze the influence of adding clamshell waste material on the mechanical properties of motorcycle disc brake pads. The research utilized an experimental approach, conducting tensile and friction tests on six samples with different compositions: 100% brake pads, 40% brake pads, 60% simping clamshell, 60% brake pads, 40% simping clamshell, 20% brake pads, 80% simping clamshell, 50% brake pads, 50% simping clamshell, and 100% brake pads. The results indicate that the sample comprising 50% used brake pads and 50% simping clamshell exhibited the smallest difference in thickness, measuring 0.05 mm or 0.59%, indicating the strongest adhesive strength and wear resistance compared to other variations. Thus, a higher simping clamshell composition sacrifices some tensile strength but offers improved elasticity, benefiting specific braking conditions.
Evaluating Wind Deflector Effect on Cargo Vans Aerodynamic Drag Using Computational Fluid Dynamics Agus Fikri; Riyan Ariyansah; Firman Noor Hasan; Oktarina Heriyani; Rosalina; Muhammad Ghiffar Sistani
Jurnal Asiimetrik: Jurnal Ilmiah Rekayasa Dan Inovasi Volume 6 Nomor 2 Tahun 2024
Publisher : Fakultas Teknik Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/asiimetrik.v6i2.6073

Abstract

Suboptimal design and body shape in freight transport vehicles can lead to increased aerodynamic drag. To address this issue, the use of wind deflectors is proposed as a solution to reduce aerodynamic resistance in cargo vans. The methodology employed in this research involves Computational Fluid Dynamics (CFD) simulations using the Ansys Fluent R2 2023 software. CFD simulations were conducted on the design of a cargo box vehicle with variations in Wind Deflector Models 1, 2, and 3, employing identical boundary condition parameters. The results of the CFD simulation for Wind Deflector Model 3 exhibited the lowest drag force at 1.1531116 Newton and a drag coefficient of 0.37031338. In conclusion, a comprehensive analysis of the CFD simulation results provides valuable insights into the intricate aerodynamic implications of Wind Deflector variations on cargo vans. Therefore, it is concluded that Wind Deflector Model 3 emerges as the optimal choice, showcasing superior aerodynamic characteristics.
Penerapan Business Intelligence Untuk Menganalisa Data Gempa Bumi di Indonesia Menggunakan Tableau Public Diana Fitri Lessy; Arry Avorizano; Firman Noor Hasan
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 4 No. 2 (2022): Desember 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i2.5316

Abstract

One of the natural disasters that often occurs in Indonesia is an earthquake. This is because Indonesia's geological position is between 3 important lithospheric plates, namely the Pacific, Eurasian and Indo-Australian plates. The forces between the plates are constantly changing, dampening disturbances both on land and at sea. This study aims to focus on visualizing earthquake data in Indonesia and implementing Business Intelligence to display earthquake area data, depth and magnitude. The method of this study uses the Tableau Public platform to process earthquake datasets in Indonesia obtained through www.kaggle.com for the period 01 January 2018 to 30 September 2022. This research produces a report in the form of a dashboard that contains data visualization for the earthquake area, depth and magnitude from various regions in Indonesia that can be used to assist in decisions to be taken. Various designs for dashboards can be used in Tableau to make data easier to read and understand.
Co-Authors Abdillah, Allif Rizki Abdul Syakir Achmad Ramadhan Achmad Sufyan Aziz Afandi, Irfan Ricky Affandi, Irfan Ricky Afikah, Prista Afnan Sabili, Dian Ainurrafik Agus Fikri Agus Fikri Ahmad Rizal Dzikrillah Ahmad Rizal Dzikrillah Ahmad Roshid Ahmad Syahril Ahmad Syahril Al Ghozi, Dhiyauddin Alfandi Safira Alim, Endy Sjaiful Allif Rizki Abdillah Allif Rizki Abdillah Allif Rizki Abdillah Ammar Rusydi Ananda Prasta Warasati Janah Ananda, Ridha Faiz Andika Saputra Andriani, Vivi Andriyani, Widyastuti Anhari, Tirta Anwar Hidayat Ari Wibowo Arief Wibowo Arien Bianingrum Rossianiz Arvin Rafialdo Aulia, Muhammad Fathan Avorizano, Arry Azhar Haikal Anwar Azhar Haikal Anwar Azis Styo Nugroho Bagas Kembar Rezkyllah Bahrul Rozak Bahrul Rozak Bisma Indrawan Dan Mugisidi Dandie Triyanto Desty Afni Dewi Mayangsari Dian Ainurrafik Afnan Sabili Dian Ainurrafik Afnan Sabili Diana Fitri Lessy Diana Fitri Lessy Dimas Febriawan Dimas Febriawan Dimas Febriawan Dion Parisda Ray Djeli Moh Yusuf Doni Gunawan Rambe E Erizal Erizal Erizal Estu Sinduningrum Estu Sinduningrum Fachri Zaini Fadli Al Gani Fadli Hardiyanto Putra Fadli, Khairul Faisal Parsakh Nursyamsi Faisal Parsakh Nursyamsyi Fajar Sidik Faldy Irwiensyah Faldy Irwiensyah Faldy Irwiensyah, Faldy Farhan Bias Purnama Putra Farhan Nufairi Farhan Nufairi Fathurrohman, Sewin Fauzan Setya Ananto Fauzi Kurniawan Fayakun Kun Febriandirza, Arafat Febriawan, Dimas Gusnul Mahesa Hafizh Dhery Al Assyam Handika, Yusuf Hanif, Isa Faqihuddin Hardyatman, Intan Diah Hazbi Santoso Hibatullah Faisal Hibatullah Faisal Hibatullah Faisal Hilmi Ammar Hilmy Zhafran Muflih I Ketut Sudaryana, I Ketut Ibnu Suhada Indra Ramadhan Indra Ramadhan Indriyanti, Prastika Intania Widyaningrum Irawati Irawati Irfan Ricky Afandi Irfan Ricky Affandi Irma Wahyuningtyas Isnan Wisnu Prastiyo Kamayani, Mia kivandi Nugroho Krisna, Mohammad Dito Dwi Kurniyati Nur Lathifah Dini Rachmawati Lingga Lingga Lingga Lita Astri Pramesti Luqman Abdur Rahman Malik Lutfi Triyuli Evana Rizki Luthfi Akbar Ramadhan M. Asep Rizkiawan Meliyawati MILASARI, LISA ASTRIA Mohammad Akhdaan Juliandra Muchammad Sholeh Muchammad Sholeh Muflih, Hilmy Zhafran Muhamad Saiful Arif Muhammad Abid Fajar Muhammad Ardhi Ryan Saputra Muhammad Ghiffar Sistani Muhammad Ikhwan Muhammad Ikhwan Muhammad Rafly Al Fattah Zain Muhammad Ridwan Muhammad Rifansyah Mukti, Avis Tantra Mutiara Zahra Arifin Nanang Juhandi Hermawan Neneng Siti Maryam Nisa Qonita Rizkina Nofendri, Yos Nugroho, Dendy Aprilianto Nunik Pratiwi Oktarina Heriyani Pamungkas, Dimas Panji Islami Anakku Pavita, Rachma Pranata, Ananda Bagas Prisilia Talakua Prista Afikah Purnamaningsih, Ine Rahayu Putri, Kirana Alyssa Rafli Erlangga Rahman Malik, Luqman Abdur Rahmatullah, Ahmad Faiz Ramadhita, Nindia Fitri Ramzah, Harry Reisa Inayah Rian gustini Ridwan Bagus Andreyanto Ridwan Maulana Subekti Rika Nurhayati Riyan Ariyansah Rizki Alamsyah Rizki Kamelia Rizky Ramdhani Rosalina Rosalina Rozak, Bahrul Saputra, Ramadani Sari, Jessica Windi Sari, Laila Atikah Setiawan, Ahmat Sewin Fathurrohman Simamora, Silvia Damayanti Sinduningrum, Estu Sistani, Muhammad Ghiffar Siti Nurhaliza Sri Fitriani Sunata, Muhamad Hafidz Ardian Syahri, Alfi Tasya Rizki Salsabilla Tia Anggita Sari Transiska, Dwi Wahyu Stiyawan Wahyuningtyas, Irma Wanda Aulia Windi Al Azmi Wulandari, Sania Zahra, Khofifah Humaeroh Az Zaini, Fachri Zuhri Halim Zuhri Halim, Zuhri